↓ Skip to main content

Predicting Out-of-Office Blood Pressure in the Clinic for the Diagnosis of Hypertension in Primary Care

Overview of attention for article published in Hypertension (Highwire), February 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
26 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
26 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Predicting Out-of-Office Blood Pressure in the Clinic for the Diagnosis of Hypertension in Primary Care
Published in
Hypertension (Highwire), February 2018
DOI 10.1161/hypertensionaha.117.10244
Pubmed ID
Authors

Mark Monahan, Sue Jowett, Kate Lovibond, Paramjit Gill, Marshall Godwin, Sheila Greenfield, Janet Hanley, F.D. Richard Hobbs, Una Martin, Jonathan Mant, Brian McKinstry, Bryan Williams, James P. Sheppard, Richard J. McManus

Abstract

Clinical guidelines in the United States and United Kingdom recommend that individuals with suspected hypertension should have ambulatory blood pressure (BP) monitoring to confirm the diagnosis. This approach reduces misdiagnosis because of white coat hypertension but will not identify people with masked hypertension who may benefit from treatment. The Predicting Out-of-Office Blood Pressure (PROOF-BP) algorithm predicts masked and white coat hypertension based on patient characteristics and clinic BP, improving the accuracy of diagnosis while limiting subsequent ambulatory BP monitoring. This study assessed the cost-effectiveness of using this tool in diagnosing hypertension in primary care. A Markov cost-utility cohort model was developed to compare diagnostic strategies: the PROOF-BP approach, including those with clinic BP ≥130/80 mm Hg who receive ambulatory BP monitoring as guided by the algorithm, compared with current standard diagnostic strategies including those with clinic BP ≥140/90 mm Hg combined with further monitoring (ambulatory BP monitoring as reference, clinic, and home monitoring also assessed). The model adopted a lifetime horizon with a 3-month time cycle, taking a UK Health Service/Personal Social Services perspective. The PROOF-BP algorithm was cost-effective in screening all patients with clinic BP ≥130/80 mm Hg compared with current strategies that only screen those with clinic BP ≥140/90 mm Hg, provided healthcare providers were willing to pay up to £20 000 ($26 000)/quality-adjusted life year gained. Deterministic and probabilistic sensitivity analyses supported the base-case findings. The PROOF-BP algorithm seems to be cost-effective compared with the conventional BP diagnostic options in primary care. Its use in clinical practice is likely to lead to reduced cardiovascular disease, death, and disability.

Twitter Demographics

The data shown below were collected from the profiles of 26 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 31%
Student > Ph. D. Student 4 15%
Student > Bachelor 4 15%
Other 3 12%
Unspecified 3 12%
Other 4 15%
Readers by discipline Count As %
Medicine and Dentistry 11 42%
Unspecified 10 38%
Engineering 2 8%
Neuroscience 1 4%
Computer Science 1 4%
Other 1 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 August 2019.
All research outputs
#1,003,088
of 13,855,981 outputs
Outputs from Hypertension (Highwire)
#391
of 4,927 outputs
Outputs of similar age
#43,471
of 399,581 outputs
Outputs of similar age from Hypertension (Highwire)
#9
of 82 outputs
Altmetric has tracked 13,855,981 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,927 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 399,581 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.